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An Improved Genetic Algorithm for Solving Multi Depot Vehicle Routing Problems

机译:求解多车场车辆路径问题的改进遗传算法

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摘要

The classical Vehicle Routing Problem (VRP) tries to minimise the cost of dispatching goods from depots to customers using vehicles with limited carrying capacity. As a generalisation of the TSP, the problem is known to be NP-hard and several authors have proposed heuristics and meta-heuristics for obtaining good solutions. The authors present genetic algorithm-based approaches for solving the problem and compare the results with available results from other papers, in particular, the hybrid clustering based genetic algorithm. The authors find that the proposed methods give encouraging results on all these instances. The approach can be extended to solve multi depot VRPs with heterogeneous fleet of vehicles.
机译:经典的车辆路径问题(VRP)试图最大程度地减少使用载重能力有限的车辆从仓库向客户分发货物的成本。作为TSP的概括,已知该问题是NP难题,几位作者已提出启发式方法和元启发式方法以获得良好的解决方案。作者提出了用于解决问题的基于遗传算法的方法,并将结果与​​其他论文的可用结果进行了比较,特别是基于混合聚类的遗传算法。作者发现,所提出的方法在所有这些情况下都给出了令人鼓舞的结果。该方法可以扩展为解决具有异构车辆群的多仓库VRP。

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